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Sustainable container distribution by alternatively fueled vehicles under customer and technical constraints

IFAC-PapersOnLine 2022年第10期55卷 836-841页

作者： Sezgi Tekil-Ergün Erwin Pesch Katarzyna Anna Kuzmicz Institute of Information Systems Faculty III University of Siegen Siegen Center for Advanced Studies in Management HHL Leipzig Graduate School of Management Leipzig Germany Faculty of Engineering Management Bialystok University of Technology Bialystok Poland

The scale of freight forwarding to the hinterland becomes an issue from the perspective of both – transport policy and cost efficiency of service providers. This problem is sharply visible in areas where ports, depots, inland intermodal terminals, exporters and importers are located, and full and empty containers satisfying demand and supply are frequently distributed creating a lot of traffic. Therefore solutions meeting the challenges of sustainable transport, responding to climate change and regulation of CO2 emissions are in need. In this paper, a variant of a mixed Fleet Heterogeneous Dial-a-Ride Problem is proposed for optimal routing of trucks carrying full and empty 20-foot and 40-foot containers, with multiple pick-ups and deliveries. Transportation is performed by alternatively fueled vehicles (AFVs) for environmental reasons which causes a constraint of a limited driving range and a need of refueling. The main objective is minimising the total distance subject to matching the empty container demand and supply, necessary refueling of the trucks, and service time windows.

关键词： heterogeneous dial-a-ride problem full empty container transportation green vehicle routing problem mixed-integer programming Lagrange relaxation

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A decomposition-based approach for the selection of standardized modular containers

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2014年第15期52卷 4660-4672页

作者： Lin, Yen-Hung Meller, Russell D. Ellis, Kimberly P. Thomas, Lisa M. Lombardi, Barbara J. Univ Arkansas Ctr Excellence Logist & Distribut Fayetteville AR 72701 USA Univ Arkansas Dept Ind Engn Fayetteville AR 72701 USA Virginia Tech Grado Dept Ind & Syst Engn Blacksburg VA USA

The standardisation of packaging and containers for product handling has potential benefits from transportation, material handling and environmental perspectives. Likewise, standardised modular containers play an important role in the Physical Internet (PI). To support implementation of standard modular containers, we introduce a mathematical model to select a requisite number of modular containers to pack a set of products to maximise space utilisation. A decomposition-based solution methodology is developed and presented. Computational results from industry-based problem instances indicate that using standardised modular containers results in increased space utilisation at the unit load level. This finding substantiates the use of modular containers in moving toward the PI.

关键词： logistics distribution Physical Internet mixed-integer programming

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A heuristic approach for scheduling activities with 'OR'-precedence constraints at an underground mine

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INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT 2020年第10期34卷 748-762页

作者： Nancel-Penard, Pierre Morales, Nelson Rojas, Valentina Gonzalez, Tomas Univ Chile Fac Phys & Math Sci Dept Min Engn Delphos Mine Planning Lab Santiago Chile Univ Chile Adv Min Technol Ctr Santiago Chile

Medium-term development planning of underground mines requires scheduling multiple activities to comply with long-term milestones, and to obtain a time span as short as possible. However, the planning must also respect the availability of construction resources and precedence constraints, which in our case can be disjunctive, that is with more than one alternative predecessor. In this paper, we present an optimisation model to find the schedule of minimum length, satisfying all the constraints mentioned. We develop a heuristic approach to solve it and show that it can be used to produce feasible development plans in a real mine.

关键词： Underground mine planning mixed-integer programming heuristic 'OR'-precedence constraints mine development

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Energy Demand Response of Process Systems through Production Scheduling and Control

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IFAC-PapersOnLine 2015年第8期48卷 385-390页

作者： Chudong Tong Nael H. El-Farra Ahmet Palazoglu Department of Chemical Engineering and Materials Science University of California Davis CA 95616 USA

Demand response has become a topic of significant research, development, and deployment over the last few years. The energy demand management is a critical task in industrial process systems for the potential benefits to be realized by promoting the interaction and responsiveness of process operation. However, the dynamic behavior, especially transition trajectories, of the underlying process is seldom taken into account during this task. Furthermore, the incorporation of energy constraints related to electricity pricing and availability is one of the key challenges in this process. The purpose of this study is thus to present a novel optimization formulation for energy demand management in dynamic process systems that takes transition behavior and cost explicitly into account, while simultaneously handling time-sensitive electricity prices. This is accomplished by bringing together production scheduling and transition control through a real-time optimization framework. The dynamic formulation is cast as a mixed-integer nonlinear programming problem and demonstrated using a continuous stirred tank reactor example where the energy required is assumed to be roughly proportional to the material flow.

关键词： Demand Response Energy systems Production Scheduling Control mixed-integer programming Chemical Processes

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BnB-DAQP: A mixed-integer QP Solver for Embedded Applications

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IFAC-PapersOnLine 2023年第2期56卷 7420-7427页

作者： Daniel Arnström Daniel Axehill

We propose a mixed-integer quadratic programming (QP) solver that is suitable for use in embedded applications, for example, hybrid model predictive control (MPC). The solver is based on the branch-and-bound method, and uses a recently proposed dual active-set solver for solving the resulting QP relaxations. Moreover, we tailor the search of the branch-and-bound tree to be suitable for embedded applications on limited hardware; we show, for example, how a node in the branch-and-bound tree can be represented by only two integers. The embeddability of the solver is shown by successfully running MPC of an inverted pendulum on a cart with contact forces on an MCU with limited memory and computing power.

关键词： mixed-integer programming embedded optimization model predictive control

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On MINLP Heuristics for Solving Shale-well Scheduling Problems

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IFAC Proceedings Volumes 2014年第3期47卷 2721-2726页

作者： Brage R. Knudsen Shaurya Sharma Bjarne Foss Department of Engineering Cybernetics Norwegian University of Science and Technology N-7491 Trondheim Norway

This paper describes mixed integer nonlinear programming (MINLP) heuristics for solving dynamic scheduling problems in complex petroleum production systems with a network topology. We modify the Feasibility Pump heuristic for convex MINLPs [Bonami and Gonçalves, 2010] by formulating a multiobjective problem, in which we aim at balancing the two goals of quickly obtaining a feasible solution and preserving solution quality with respect to the objective value. We further present a simple linearization-based heuristic, only aimed at quickly generating feasible solutions. The MINLP heuristics are applied to a dynamic multi-pipeline shale well and compressor scheduling problem, targeted on application in decision-support tools for improving operations in large shale-gas systems. Developing efficient and robust heuristics are important for the applicability of these tools, in the sense that low computation times are often more important than global optima. A computational study shows that the proposed objective-oriented Feasibility Pump is competitive both in terms of solution quality and computation time compared to other heuristics and the branch-and-bound method.

关键词： Heuristics Scheduling mixed-integer programming Shale-gas production

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A progressive hedging-based matheuristic for the stochastic production routing problem with adaptive routing

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COMPUTERS & OPERATIONS RESEARCH 2024年 169卷

作者： Kermani, Ali Cordeau, Jean-Francois Jans, Raf HEC Montreal CIRRELT 3000 chemin Cote-Sainte-Catherine Montreal PQ H3T 2A7 Canada GERAD 3000 chemin Cote Sainte Catherine Montreal PQ H3T 2A7 Canada

The production routing problem (PRP) arises in the context where a manufacturing facility manages its production schedule, the delivery of goods to customers by a fleet of vehicles, and the inventory levels both at the plant and at the customers. The presence of uncertainty often complicates the planning process. In particular, production and distribution costs may significantly increase if demand uncertainty is ignored in the planning phase. Nevertheless, only a few studies have considered demand uncertainty in the PRP. In this article, we propose a two-stage stochastic programming approach for a one-to-many PRP with a single product and demand uncertainty. Unlike previous studies in the literature, we consider the case where routing decisions are made in the second stage after customer demands become known. This offers more flexibility, which can decrease transportation costs by preventing unnecessary customer visits. In addition to the static-dynamic case, in which setup decisions are made first and production quantities are decided in the second stage, we also consider the static-static setting where both sets of decisions must be made prior to the demand realization. A progressive hedging algorithm combined with a matheuristic is developed to solve the problem. The role of the progressive hedging algorithm is to decompose the stochastic problem into more tractable scenariospecific subproblems and lead the first-stage variables towards convergence by modifying their Lagrangean multipliers. However, solving the subproblems remains challenging since they include routing decisions, and we thus propose a matheuristic to exploit the structural characteristics of the subproblems. First, a Traveling Salesman Problem (TSP) is solved to find the optimal tour for all customers regardless of demand and capacity. Utilizing the sequence obtained from the TSP, we then solve a restricted PRP while taking into account the other constraints of the original problem. Finally, for

关键词： Production routing Stochastic programming Progressive hedging Matheuristic mixed-integer programming

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Classifying and modelling demand response in power systems

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ENERGY 2022年 242卷

作者： Morales-Espana, German Martinez-Gordon, Rafael Sijm, Jos TNO Energy Transit The Hague Netherlands Univ Groningen Fac Sci & Engn Groningen Netherlands

Demand response (DR) is expected to play a major role in integrating large shares of variable renewable energy (VRE) sources in power systems. For example, DR can increase or decrease consumption depending on the VRE availability, and use generating and network assets more efficiently. Detailed DR models are usually very complex, hence, unsuitable for large-scale energy models, where simplicity and linearity are key elements to keep a reasonable computational performance. In contrast, aggregated DR models are usually too simplistic and therefore conclusions derived from them may be misleading. This paper focuses on classifying and modelling DR in large-scale models. The first part of the paper classifies different DR services, and provides an overview of benefits and challenges. The second part presents mathematical formulations for different types of DR ranging from curtailment and ideal shifting, to shifting including saturation and immediate load recovery. Here, we suggest a collection of linear constraints that are appropriate for large-scale power systems and integrated energy system models, but sufficiently sophisticated to capture the key effects of DR in the energy system. We also propose a mixed integer programming formulation for load shifting that guarantees immediate load recovery, and its linear relaxation better approximates the exact solution compared with previous models.(c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Demand side management Demand response Linear programming mixed-integer programming Integrated energy system models Power systems models

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Capacity planning with reconfigurable kits in semiconductor test manufacturing

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2006年第13期44卷 2625-2644页

作者： Zhang, Z. Zhang, M. T. Niu, S. Zheng, L. Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Intel Corp Chandler AZ 85248 USA Intel Prod Shanghai Ltd Shanghai 200131 Peoples R China

To test an integrated circuit (IC) product, both a tester and qualified kits are simultaneously needed. One kit usually consists of six or seven components and is somewhat like a fixture. A remarkable amount of investment will be saved if one allows kit reconfigurations and purchase individual components instead of using entire kits. Unfortunately, this approach of the reconfigurable kit also increase exponentially the complexity of kit management and thus capacity planning due to intricate {product, tester, kit, component} qualification relationships. The paper describes the Automated Capacity Allocation System ( ACAS) developed at Intel Shanghai for generating an optimal capacity and kit-allocation plan for a 9-week horizon. It performs optimization at the component level using mixed-integer programming (MIP) technology. High Buffer Formulation and Tight Workload Formulation are introduced to determine the number of kits needed to guarantee a feasible capacity plan. Detailed analyses of parameter setting, objective prioritizing and formulation comparison were also conducted. With the implementation of the ACAS at Intel, we have already realized millions of dollars in savings from kit purchasing and about 90% man-hour savings in the capacity planning.

关键词： semiconductor manufacturing capacity planning mixed-integer programming kit

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Multi-objective Maintenance Workforce Scheduling in a Steel Company

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IFAC Proceedings Volumes 2009年第4期42卷 1049-1054页

作者： N. Safaei D. Banjevic A.K.S. Jardine C-MORE Department of Mechanical and Industrial Engineering University of Toronto Canada (Tel: 416-978-7602)

In this paper, a real maintenance workforce scheduling problem is formulated as a multi-objective mixed-integer programming model with the aim of simultaneous minimizing the workforce cost and maximizing the equipment availability. The workforce is provided by the internal and external resources using the regular time, overtime and contracting. The equipment availability is measured using the downtime due to the preventive maintenance (scheduled) and failure repair (unscheduled) jobs. The priority of the imminent or potential failures can be different because of the severity effect of the failures on the system. Hence, the total weighted flow time is used as a scheduling criterion to measure the equipment availability. The proposed model is verified using a comprehensive numerical example and the obtained results are discussed.

关键词： Scheduling Workforce planning Maintenance Multi-objective optimization mixed-integer programming

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